Long Memory in Financial Time Series: Estimation of the Bivariate Multi-Fractal Model And Its Application For Value-at-Risk
نویسندگان
چکیده
Long memory (long-term dependence) seems to be as widespread in financial time series as in nature. Inspired by the long memory property, Multi-fractal processes have recently been introduced as a new tool for modeling the stylized facts in financial time series. In this paper, we attempt to construct a bivariate multi-fractal model, and implement its estimation via both GMM and likelihood approaches. For its empirical assessment, we apply the model on portfolio investment concerning VaR using time series of foreign exchange rates and bond maturity rates. Keyword: Long memory, Bivariate Multifractal, GMM estimation, VaR. JEL Classification: C20, G15 Correspondence: Department of Economics, University of Kiel, Olshausenstr. 40; 24118 Kiel, Germany, Email: ∗[email protected].
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